Top AI Jobs in Los Angeles, CA

Leads Samsara’s GTM AI Engineering team, building production AI agents, copilots, workflow automations, predictive models, and evaluation systems. Owns the shared AI platform, architecture, governance, observability, model routing, cost controls, and CRM intelligence. Partners with Sales, Customer Success, Support, Product, and Engineering to drive adoption and measurable business impact. This hands-on director role involves coding and prototyping approximately 70% of the time while hiring, developing, and guiding the engineering team.

The Principal AI/ML Engineer will lead the development of AI/ML platforms, drive technology architecture, ensure quality and integration, and provide strategic leadership while managing a team of engineers.

Leads OuterBox’s internal AI strategy, AI engineering team, and development of client-facing AI services. Identifies market opportunities, converts internal capabilities into priced consulting offerings, oversees production deployments and partner programs, and drives AI adoption, training, and measurement. Partners with executives, clients, engineering, and technology teams on architecture, security, cloud governance, reliability, pricing, and ROI.

Set the technical direction for Rapid7’s LLM and agentic AI systems. Lead architecture, model strategy, fine-tuning, post-training, inference optimization, evaluation standards, and complex cross-team initiatives. Build critical model and inference code, mentor senior engineers, resolve technical trade-offs, and influence product and platform strategy across cybersecurity products.

Sets Rapid7’s company-wide AI technology vision, architecture strategy, and multi-year roadmap for security products. Leads production LLM and agentic AI initiatives, establishes engineering, evaluation, and responsible-AI standards, and guides model and infrastructure investments. Partners with executives, mentors senior engineering leaders, solves high-impact technical challenges, and represents Rapid7 externally. The role spans LLMs, predictive AI, classical machine learning, distributed systems, and scalable AI production infrastructure.

Designs, builds, and ships production LLM and agentic AI systems for cybersecurity products. Leads architecture, model strategy, fine-tuning, post-training, inference optimization, evaluation, and technical roadmaps. Establishes engineering practices, mentors engineers, leads design reviews, prototypes critical model and training code, and partners cross-functionally to deliver scalable, cost-effective AI solutions.

Leads Boomi’s enterprise AI strategy, agentic AI transformation, and AI data foundation. The role oversees multi-agent architecture, model strategy, AI gateways, knowledge graphs, semantic layers, retrieval, trust and governance systems, evaluation, observability, and production data pipelines. It manages and mentors distributed AI and data engineering teams, drives enterprise adoption, defines architecture and operating standards, and communicates strategy to executives, customers, and partners.

Provide bilingual Somali-English support to learners in a virtual data annotation program. Facilitate labeling practice, answer questions, review and grade multimodal annotation assignments, conduct office hours, create walkthroughs, monitor learner progress, provide feedback, and escalate attendance or performance concerns. TAs must understand annotation guidelines, AI output evaluation, quality assurance, secure data handling, and AI training fundamentals.

Own the enterprise AI strategy, roadmap, governance, investment priorities, and measurement framework. Identify and prototype high-value AI use cases, guide pilots into production, establish responsible-AI standards for sensitive data, and communicate outcomes to executives. Build adoption through enablement and reusable practices while coordinating technology, business, legal, security, data, and vendor partners. Lead the emerging AI strategy function and hold teams accountable for delivery and value realization.

Serves as a hands-on technical leader for emerging technology and AI experimentation. Designs prototypes, proofs of concept, pilots, integrations, and architecture evaluations; writes and reviews prototype code; troubleshoots complex technical issues; and develops reusable standards and recommendations. Collaborates with architecture, security, data, risk, legal, procurement, vendors, and delivery teams to transition validated concepts into scalable solutions. Mentors engineers and communicates findings, tradeoffs, risks, and adoption recommendations to technical and business stakeholders.

Build and operate Affirm’s AI platform, including LLM and MCP gateways, agent runtimes, evaluation services, and governance controls. Design highly available backend systems, manage identity, quotas, routing, caching, reliability, observability, and security for AI workloads. Own projects from design through launch and on-call, establish engineering standards, collaborate across teams, mentor engineers, and help scale AI systems into production.

Leads Year Up United’s AI innovation portfolio, maintaining visibility into initiatives, managing intake and governance, running low-cost pilots, and making evidence-based go/kill decisions. The role evaluates emerging AI capabilities, builds organizational AI fluency through communities and Champions, partners cross-functionally, and hands validated pilots to technical teams for scaling. It also includes mentoring students and occasional travel to organizational sites.

Lead the architecture and development direction of NVIDIA ALCHEMI and related AI software for chemistry and materials science. Design developer tools, APIs, and workflows; translate advances in machine learning, generative modeling, interatomic potentials, and quantum chemistry into product capabilities; coordinate researchers, engineers, product teams, partners, and customers; and represent NVIDIA at scientific and industry events.

As a Senior Solutions Architect, you will assist customers in building solutions with NVIDIA's AI technology, focusing on Generative AI and Large Language Models while collaborating across teams for performance analysis.

Lead hardware-software co-design for LLM inference: drive and document architecture, build executable C++ hardware models, optimize performance with good algorithms and parallelism, diagnose cross-team chip and subsystem issues, and automate workflows to improve efficiency.

Define and drive CrowdStrike’s company-wide AI and agentic architecture. Design production AI systems, shared platforms, lifecycle workflows, and developer tooling across products and business units. Improve performance, resilience, scalability, observability, governance, security, and auditability across cloud and edge environments. Build reference implementations, guide architectural decisions, resolve complex engineering challenges, mentor technical leaders, and align senior stakeholders around AI strategy and implementation.

Set technical direction for Root’s AI platform, including infrastructure, tooling, shared services, governance, reliability, security, observability, and cost management. Lead cross-team initiatives, guide AI and LLM architecture decisions, establish operating standards, shape technical roadmaps, resolve complex tradeoffs, and mentor engineers and technical leaders across the organization.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Lead product vision and strategy for an end-to-end AI-powered software factory. Integrate planning, coding, review, and verification across GitLab Duo Agent Platform and product areas. Collaborate with engineering, design, and GTM teams, identify gaps and dependencies, present recommendations to executives, and drive execution to deliver cohesive developer workflows.

Build and deploy production-grade generative AI and agentic systems for enterprise clients. Responsibilities include identifying high-value business problems, shaping architecture, developing multi-agent workflows, APIs, data pipelines, integrations, and distributed systems, and owning solutions from discovery through deployment. The role requires hands-on ownership of evaluation, observability, security, reliability, scalability, latency, and cost, along with direct collaboration and communication with senior client leaders.

Own the roadmap and delivery of LawnStarter’s conversational AI and agent experiences for homeowners and service Pros. Lead customer and Pro chat, agentic actions, messaging, human handoffs, external AI-agent integrations, evaluations, and safety guardrails. Launch production AI products that perform real marketplace actions such as bookings, skips, and rescheduling. Partner cross-functionally with engineering, applied science, design, data, support, and operations while measuring resolution, satisfaction, accuracy, productivity, and retention.

Designs, develops, and supports digital tools, automated workflows, dashboards, data integrations, and AI-enabled applications for legal services and law firm operations. Responsibilities include requirements gathering, solution delivery, Power Platform development, AI agent configuration, testing, documentation, project management, stakeholder engagement, training, adoption, and responsible evaluation of emerging technologies. The role requires collaboration with attorneys, business teams, data specialists, vendors, and governance stakeholders while protecting confidential and client information.

Deploys and integrates Circadia’s AI platform with healthcare customers, tailoring predictive and LLM-based workflows to clinical and operational needs. Builds EHR, care-coordination, billing, and compliance integrations; troubleshoots production and data-quality issues; collaborates with clinical stakeholders and internal teams; and develops reusable onboarding tools, documentation, and deployment playbooks.

Designs and deploys AI-powered features and scalable AI/ML services across SaaS products. Responsibilities include translating business problems into AI solutions, integrating large language models, preparing data, evaluating model performance, writing Python, building secure deployment infrastructure, and collaborating with product, data, and cloud operations teams. The role requires production AI/ML experience, scalable data infrastructure expertise, AWS familiarity, and modern DevOps practices.

Leads CDW’s AI advisory consulting portfolio, including strategy, governance, operating models, adoption, prioritization, and roadmaps. Develops consulting methodologies, delivery frameworks, sales enablement, and thought leadership. Advises executives and customers, leads complex presales pursuits, shapes proposals and business cases, oversees delivery quality and risk, evaluates technical feasibility, and mentors consulting and presales teams.